Image signatures are image features for discriminating (determining the identity of) images. By comparing an image signature extracted from an image with an image signature extracted from another image, an identity scale (in general, referred to as similarity or distance) indicating a degree of the two images being identical can be calculated from a comparison result. Further, by comparing the calculated identity scale with a threshold, it is possible to determine whether or not the two images are identical. In this context, the meaning of “two images being identical” includes not only the case where the two images are identical at the level of image signals (pixel values of the pixels constituting the images), but also the case where one image is a duplicate image of the other by means of various alteration processes such as conversion of compression format of an image, conversion of size/aspect ratio of an image, adjustment of color tone of an image, various filtering processes (sharpening, smoothing, and the like) applied to an image, local processing (caption superimposition, cutout, and the like) applied to an image, and recapturing of an image. By using image signatures, as it is possible to detect duplication of an image or a moving image which is a collection of images, for example, image signatures are applicable to an illegal copy detection system for images or moving images.
Examples of image signatures are described in Non-Patent Document 1, Non-Patent Document 2, and Patent Document 1. The methods described in these documents include extracting features for a plurality of local regions of an image, quantizing the extracted features to calculate quantization indexes, and using the calculated quantization indexes for the respective local regions as a quantization index vector to use as an image signature.
Specifically, in Non-Patent Document 1 and Non-Patent Document 2, an image is divided into blocks. Each of the blocks is used as a local region, and a feature (quantization index) is extracted. Further, in Non-Patent Document 1, luminance distribution patterns within a block are classified into eleven types and are used as quantization indexes. In Non-Patent Document 2 (art described as “Local Edge Representation” in Non-Patent Document 2), a position of center of gravity of an edge point, extracted from a block, is quantized to be used as a quantization index.
On the other hand, as shown in FIG. 12, the method described in Patent Document 1 includes respectively calculating mean luminance values from thirty two pieces of rectangle regions 244 (among them, sixteen pieces of rectangle regions are shown in FIG. 12) at predetermined positions in an image 240, and calculating differences in mean luminance value between rectangle regions forming pairs (the paired rectangle regions are linked to each other with dotted lines 248 in FIG. 12), to thereby obtain difference vectors 250 in sixteen dimensions. With respect to the difference vectors 250, a composite vector is generated by means of vector transformation, and a quantization index vector in sixteen dimensions, acquired by quantizing the respective dimensions of the composite vector, is used as an image signature.    Patent Document 1: Japanese Unexamined Patent Publication No. 8-500471    Non-Patent Document 1: Kota Iwamoto, Eiji Kasutani, Akio Yamada, “Image Signature Robust to Caption Superimposition for Video Sequence Identification”, Proceedings of International Conference on Image Processing (ICIP2006), 2006    Non-Patent Document 2: Arun Hampapur, Ruud M. Bolle, “Comparison of Distance Measures for Video Copy Detection”, Proceedings of International Conference on Multimedia and Expo (ICME2001), p. 946, 2001